Chinese Internet Finance Credit Investigation Issue and Legal Countermeasures

Chinese Internet Finance Credit Investigation Issue and Legal Countermeasures

Cheng-Yong Liu (Beijing Institute of Technology – Zhuhai, China) and Ruey-Cheng Chen (National Taiwan University, Taiwan)
Copyright: © 2019 |Pages: 26
DOI: 10.4018/978-1-5225-7808-6.ch008

Abstract

In recent years there has been a phenomenon of “Thirst for Credit Investigation Information” within China's internet finance industry. To compensate for the new credit investigation demands that traditional measures of credit investigation lack, big data credit investigation has been widely recognized as a viable solution. Big data credit investigation however poses greater risks to the rights and interests of the information subject. In order to solve the existing problems associated with the data credit investigation industry, the author advocates that special laws and regulations be revised or formulated on the basis of balancing the rights and interests of the information subject with those of public interests. In the future, the combination of big data credit investigation system with blockchain technology may effectively solve the problems that are harmful to the rights and interests of the information subject, such as information-isolated island and information security.
Chapter Preview
Top

Background

Big data credit investigation is often referred to as internet credit investigation or network credit investigation. Compared to traditional credit investigation agencies, the Credit Investigation Center of PBOC for example, has been widely used in the credit risk management of financial agencies.1 By the end of May 2017, a total of 3,000 agencies had been connected to the database, which included relevant information of 926 million individuals, 23.71 million enterprises and other organizations, effectively solving the problem of information asymmetry and improving the convenience of public financing (Xinhua News Agency, 2017). However, it is difficult for the centre to fully collect information on the liabilities of people with debts outside financial agencies. To prevent the risk of credit default from moving across markets, industries or regions, it is necessary to cultivate some social credit investigation agencies outside the Credit Investigation Center of PBOC,2 so as to build a diversified and comprehensive credit investigation system compatible with market demands (People's Bank of China, 2017). The big data credit investigation industry has been rapidly developing in China in recent years (Wang Qiang, Qing Sude & Ba Jieru, 2017). It is important to note that credit system based on the big data is only part of the Chinese credit information system, and it is still unable to replace the traditional credit information. For the complete evaluation of the credit status of a specific person, it is still necessary to combine the traditional credit report with big data, the credit report can then be completed. The importance of a credit system based on big data cannot be overemphasized nor can the importance of traditional credit reporting methods.

Key Terms in this Chapter

Identification of the Information Subject: Includes direct and indirect identification. Direct identification can point to a specific individual based on the information itself, such as ID number, telephone number, home address, etc. Indirect identifiability refers that it can point to a specific individual after combining the information with other information.

Traditional Credit Investigation Agencies: Combining with the identity verification of the identity authentication center, the credit investigation agencies can provide credit inquiring services to the banking system and personal credit reports to individuals by using the data submitted by commercial banks and other social organizations.

Minimum Adequacy Principle: Requires that personal information should be collected and processed only within the minimum limit of the legal target.

Information Subject's Right to Know: Any civil subject, whose information has been collected by big data credit investigation agencies, has the right to know the collected information as well as the specific contents and forms of credit investigation products produced according to the information.

Credit Information: Refers to the information produced when the information subject participates in the social economic activities. This information is obtained by the credit investigation agencies from the credit information provider and provided to the information users as the credit level of the information subject after the analysis and processing. If the information refers to personal identification information, account information, association information, public records, and bad records, personal activity information and private information that are unrelated to social and economic activities should be excluded from credit information.

Information Isolated Island: A computer application system whose functions are not related to each other, information is not shared and exchanged, and information is disconnected from business processes and application.

Big Data Credit Investigation Agencies: The credit investigation agencies that collect, sort, store and process structured data and unstructured data on the internet by using big data technology to redesign the model and algorithm of credit investigation and form specific credit products.

Personal Information: May contain (1) sensitive personal information relating to personal privacy, which is the personal information consisting of information about racial or moral origins, political views, religious beliefs or other similar beliefs, union affiliation, physical or psychological status, sexual agency or alleged agency relationship of the data objects, or related litigation, etc.; and (2) trivial personal information that does not involve personal privacy, which refers to materials that are clearly not unduly infringed on the right to privacy of the recorded person.

Complete Chapter List

Search this Book:
Reset